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Comparing several approaches for hierarchical classification of proteins with decision trees

Costa, Eduardo P. and Lorena, Ana C. and Carvalho, Andre C. P. L. F. and Freitas, Alex A. and Holden, Nicholas (2007) Comparing several approaches for hierarchical classification of proteins with decision trees. In: Sagot, Marie-France and Walter, Maria Emilia M. T., eds. Advances in Bioinformatics and Computational Biology: Second Brazilian Symposium on Bioinformatics. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 126-137. ISBN 978-3-540-73730-8. E-ISBN 978-3-540-73731-5. (doi:10.1007/978-3-540-73731-5_12) (KAR id:14556)

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http://dx.doi.org/10.1007/978-3-540-73731-5_12

Abstract

Proteins are the main building blocks of the cell, and perform almost all the functions related to cell activity. Despite the recent advances in Molecular Biology, the function of a large amount of proteins is still unknown. The use of algorithms able to induce classification models is a promising approach for the functional prediction of proteins, whose classes are usually organized hierarchically. Among the machine learning techniques that have been used in hierarchical classification problems, one may highlight the Decision Trees. This paper describes the main characteristics of hierarchical classification models for Bioinformatics problems and applies three hierarchical methods based on the use of Decision Trees to protein functional classification datasets.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-540-73731-5_12
Uncontrolled keywords: Gene Ontology; Leaf Node; Fourth Level; Main Building Block; Interpro Entry
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:04 UTC
Last Modified: 16 Feb 2021 12:26 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/14556 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
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